The Research On Meteorological Condition Early Warning And Assessment Technique Of Winter Whea Powdery Mildew

In this paper, based on meteorological records and the winter wheat powdery mildewdisease information from263weather stations located in frequent area, easy happening areaand second prone area, during1980-2010, using correlation analysis method, the key factorsand key slots which affect the wheat powdery mildew are selected to build a rolling evaluationmodel for wheat powdery mildew happening on ten-day scale at different weather conditiongrades. In terms of the typical station and regional scale, three kinds of methods （stepwiseregression, stepwise discriminant analysis, and generalized regression neural network（GRNN））are applied to construct a dynamic model for forecasting the wheat powdery mildewhappening at different weather levels on five-day scale in Hebei province. The mainconclusions are as follows:（1） The change of meteorological elements in recent30years led to more winter wheatpowdery mildew occurrence as a whole. During the winter wheat growth period, meantemperature increased at the rate of0.46℃10a^-1over last30years and the occurrence area ofcrop disease will increase by2.553million hm²Â·time when annual mean temperature increasesby1℃. The average precipitation intensity increased at the rate of0.18mm·d^-1·10a^-1and theoccurrence area of crop disease will increase by2.708million hm²Â·time when annual averagerainfall intensity increases by1mm·d^-1. The sunshine hours decreased at the rate of9.9h·10a^-1and the occurrence area of crop disease will increase by0.269million hm²Â·time when annualaverage sunshine hours increases by10h. Among the factors of sunshine change, temperaturechange and precipitation change induced by climate change, temperature increase has the mostsignificant impact on the increase of occurrence area of crop diseases, followed by thedecrease of sunshine hours and the increase of precipitation intensity. The standardizedregression coefficients of the above three factors are0.584,-0.474,0.100. （2） The rolling evaluation model for winter wheat powdery mildew occurrence underdifferent meteorological conditions, from late March to late May, was constructed and verified.The forecasting correct rate for try was100%, and the overall correct rate increased from83%to90%, whereas forecast accuracy on wheat powdery mildew incidence area rate, arose from87%to more than90%gradually. Concluded that the rolling evaluation on wheat powderymildew disease development start from the mid March, has great significance, so as to guidethe agricultural production better on the work of wheat powdery mildew prevention andcontrolling.（3） The rolling evaluation index for winter wheat powdery mildew occurrence underdifferent meteorological conditions, from late March to late May, was constructed and verified.The forecasting correct rate was more than80%. By comparison with the rolling evaluationmodel, it was more simple and convenient to use, but the precision is slightly lower than themodel.（4） The main factors affecting the wheat powdery mildew occurrence between winter andspring are average lowest temperature, warm rain coefficient and average wind speed.（5） With wheat powdery mildew disease index as predictive factors, the dynamic modelfor forecasting the wheat powdery mildew happening at different weather levels with threekinds of methods （stepwise regression, stepwise discriminant analysis, and generalizedregression neural network（GRNN））, is verified that three kinds of models to predict the correctrate all achieves80%, what will provide scientific and technological support for thedevelopment of wheat powdery mildew’s short-term forecasting, improvement of thecomprehensive prevention and control ability and the decision-making service.